Comprehensive Evaluation System for Realizing the Ability of University Piano Teaching

Ma, WeiNa

doi:10.1155/2022/6895484

Cited by 7 publications

(6 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Teachers' energy and time are limited and because they cannot identify the challenges that every student faces, it is difficult for a teacher to offer a lesson that is individualized for each student's level of proficiency [8]. In addition, because students in big classes have varying levels of competence, learning process of pupils is made more difficult by the teaching environment [9]. e use of multimedia technology in piano instruction at universities and colleges represents a significant revolution in music teaching and educational method in colleges and universities, indicating that music education has entered a new age [10].…”

Section: Overview Of Multimedia-based Piano Teaching Model (Mptm)mentioning

confidence: 99%

Training Strategy of Music Expression in Piano Teaching and Performance by Intelligent Multimedia Technology

Zheng¹,

Tian²,

Ai³

2022

International Transactions on Electrical Energy Systems

View full text Add to dashboard Cite

Teaching using a multimedia technology in the 21 s t century affords the possibility of developing novel instructional strategies and paves the way for the all-around extension of musical educational functions. The importance of multimedia teaching technology in piano instruction has started to emerge in our country and society due to the ongoing development of this kind of technology in music educational institutions here. The conventional method of teaching piano has several drawbacks that may be mitigated by using one of the several alternative methods of instruction for the instrument, especially in light of the ongoing advancements in science and technology. A pianist’s methods of expression are the tools they use to convey their thoughts and emotions about a piece of music to the audience. Teachers may demonstrate their musical skills to students and they must immediately focus on a musical expression which is vital for performers. In this paper, the Multimedia-based Piano Teaching Model (MPTM) has been proposed to improve the piano teaching quality. Traditional piano instruction is improved and developed using multimedia technology in this article. The Internet education model is used for teacher assessment, and the systematic way representing piano teaching combines different music educational materials. It begins building a sufficiently broad music network infrastructure resource sharing framework and benefits society’s amateur music literacy. The use of machine learning in students’ concrete piano instruction has the potential to thoroughly promote contemporary piano instruction and enhance the overall quality of instruction. To begin, an explanation of the intelligent piano’s features and capabilities is provided. The neural network is used to suggest a technique for detecting a piano note on a set. The network can assess the input piano music signal’s time frequency by translating the original time-domain waveform into the time-varying frequency distribution. Intelligent piano instruction analysis can effectively achieve the overall optimization of piano performance. The test results show that MPTM has a significant role in boosting the desire to learn to play the instrument. The experimental results show that the proposed MPTM achieves a learning skills ratio of 97.6%, a learning activity ratio of 98.5%, a student performance ratio of 93.8%, a teaching evaluation ratio of 90.3%, and a learning behavior ratio of 94.2% when compared to other methods.

show abstract

Section: Overview Of Multimedia-based Piano Teaching Model (Mptm)mentioning

confidence: 99%

Training Strategy of Music Expression in Piano Teaching and Performance by Intelligent Multimedia Technology

Zheng¹,

Tian²,

Ai³

2022

International Transactions on Electrical Energy Systems

View full text Add to dashboard Cite

show abstract

“…Rhythm is the movement of each tone in a song, fast or slow, long or short, strong or weak, and is an important component of a song and the core of a song's form. e quality of the rhythm directly affects the quality of the song [12]. At present, the rhythm forms of songs are mainly active and brisk, impassioned, soothing and distant, sad and dull.…”

Section: Piano Automatic Accompaniment Methodsmentioning

confidence: 99%

Designing an Automatic Piano Accompaniment System using Artificial Intelligence and Sound Pattern Database

2022

Mobile Information Systems

View full text Add to dashboard Cite

The rapid development of artificial intelligence has made various fields to have corresponding connections with it, and music plays an important role in daily life. One of the applications of artificial intelligence in the field of art is to use music generation algorithms to endow machines with the function of generating melody. This ability can provide certain assistance to musicians when composing music, so that music creators can inspire inspiration in the creative process. Researchers have done a lot of work in the automatic generation of music. The piano is widely used in the field of automatic accompaniment and has strong versatility. The main purpose of this paper is to design a piano-based automatic accompaniment system, to think of melody and harmony as a machine learning-like task. By training on a selected series of samples, a database of phonomorphic metastructures is constructed, to systematically collect the original piano accompaniment patterns by building a sound pattern database, and convert the collected original sound patterns into the original sound pattern structure and store in the database. Then, by establishing two Hidden Markov Model (HMM) systems to simulate the thinking mode of the composer’s piano accompaniment process, a melody style related to a certain collection of samples is formed. Finally, the Viterbi algorithm is used to select the appropriate piano accompaniment metastructure in the database to generate the piano accompaniment of the melody section. The experimental results of this paper show that, as far as the accompaniment generation effect is concerned, although the generation effect of this paper is slightly different, the overall difference does not change much. It shows that the effect generated by the method in this paper is relatively stable.

show abstract

“…Create a fresh teaching approach to replace the outmoded teacher-lectureheavy single-class teaching approach. The study [17] investigated whether a beginner and experienced piano students learn to play a certain kind of staccato in three different types of group training situations. Just audio and the teacher's live performance are used to show how challenging the music sounds.…”

Section: Related Workmentioning

confidence: 99%

Exploring the Reform of Piano Course Teaching based on AGIL Model

Xueying Liu

2024

jes

View full text Add to dashboard Cite

University music performance majors are strongly encouraged to take a piano fundamentals course as one of their necessary foundational topics. For college music achievement majors, it is very crucial to develop and raise students' piano playing proficiency and expertise. For the analysis and creation of complex systems, the AGIL model serves as a theoretical framework. This model may be used to create a complete methodology for piano instruction that emphasizes the growth of the student's flexibility, goal achievement, skill integration, and pause in action. Learning to play the piano may test these connections in the brain that control movement in students and people with poor motor abilities, and it can even improve coordination. Thus, we suggested the AGIL model for the reform of piano course teaching to further encourage the creative growth of piano instruction for music majors in colleges and universities in a diverse environment. The dataset used was made up of Chinese piano students. The performance measures used to assess suggested efficacy include ideal teaching, student performance, note-reading skill, teamwork ability, and student support rate. The evaluation's results indicate that the AGIL approach has provided 98.5% which seems to be useful for improving students' piano skills.

show abstract

Comprehensive Evaluation System for Realizing the Ability of University Piano Teaching

Cited by 7 publications

References 13 publications

Training Strategy of Music Expression in Piano Teaching and Performance by Intelligent Multimedia Technology

Training Strategy of Music Expression in Piano Teaching and Performance by Intelligent Multimedia Technology

Designing an Automatic Piano Accompaniment System using Artificial Intelligence and Sound Pattern Database

Exploring the Reform of Piano Course Teaching based on AGIL Model

Contact Info

Product

Resources

About